Outcome of patients with autoimmune diseases in the intensive care unit : A mixed cluster analysis

Objectives: The interest on autoimmune diseases (ADs) and their outcome at the intensive care unit (ICU) has increased due to the clinical challenge for diagnosis and management as well as for prognosis. The current work presents a-year experience on these topics in a tertiary hospital. Methods: The mixed-cluster methodology based on multivariate descriptive methods such as principal component analysis and multiple correspondence analyses was performed to summarize sets of related variables with strong associations and common clinical context. Results: Fifty adult patients with ADs with a mean age of 46.7±17.55 years were assessed. The two most common diagnoses were systemic lupus erythematosus and systemic sclerosis, registered in 45% and 20% of patients, respectively. The main causes of admission to ICU were infection and AD flare up, observed in 36% and 24%, respectively. Mortality during ICU stay was 24%. The length of hospital stay before ICU admission, shock, vasopressors, mechanical ventilation, abdominal sepsis, Glasgow score and plasmapheresis were all factors associated with mortality. Two new clinical clusters variables (NCVs) were defined: Time ICU and ICU Support Profile, which were associated with survivor and no survivor variables. Conclusions: Identification of single factors and groups of factors from NCVs will allow implementation of early and aggressive therapies in patients with ADs at the ICU in order to avoid fatal outcomes.

• Fecha de publicación: 2015
• Institución: Universidad del Rosario
• Repositorio: Repositorio EdocUR - U. Rosario
• Idioma: eng
• OAI Identifier: oai:repository.urosario.edu.co:10336/19220
• Acceso en línea: http://repository.urosario.edu.co/handle/10336/19220
• Palabra clave: antimalarial agent; disease modifying antirheumatic drug; hypertensive factor; immunoglobulin G; immunosuppressive agent; steroid; tumor necrosis factor; Enfermedades; Enfermedades autoinmunes; Cuidados intensivos
• License: Abierto (Texto Completo)